Senior Data Scientist, Healthcare

- A minimum of a 2.1 degree in Computer Science, AI, Data Science, Statistics, or a similar quantitative field. - Deep understanding and development of AI/ML models, including time series, supervised/unsupervised learning, reinforcement learning, and LLMs. - Experience with the latest AI engineering approaches such as prompt engineering, retrieval-augmented generation (RAG), and agentic AI. - Strong Python skills with a grounding in software engineering best practices (CI/CD, testing, code reviews, etc). - Expertise in data engineering for AI: handling large-scale, unstructured, and multimodal data. - Understanding of responsible AI principles, model interpretability, and ethical considerations. - Strong interpersonal skills and team working. - Demonstrable experience with modern deep learning frameworks (e.g., PyTorch, TensorFlow), fine-tuning or distillation of LLMs (e.g., GPT, Llama, Claude, Gemini), machine learning libraries (e.g., scikit-learn, XGBoost) (desirable). - Experience with data storage for AI, vector databases, semantic search, and knowledge graphs (desirable). - Actively contributes to open-source AI projects, research publications, and industry events/websites (desirable). - Familiarity with AI security, privacy, and compliance standards e.g., ISO42001 (desirable).